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Relevant bibliographies by topics / Adaptive computing systems Signal processing

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Academic literature on the topic 'Adaptive computing systems Signal processing'

Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

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Journal articles on the topic "Adaptive computing systems Signal processing"

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Pfänder, O. A., H. J. Pfleiderer, and S. W. Lachowicz. "Configurable multiplier modules for an adaptive computing system." Advances in Radio Science 4 (September 6, 2006): 231–36. http://dx.doi.org/10.5194/ars-4-231-2006.

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Abstract. The importance of reconfigurable hardware is increasing steadily. For example, the primary approach of using adaptive systems based on programmable gate arrays and configurable routing resources has gone mainstream and high-performance programmable logic devices are rivaling traditional application-specific hardwired integrated circuits. Also, the idea of moving from the 2-D domain into a 3-D design which stacks several active layers above each other is gaining momentum in research and industry, to cope with the demand for smaller devices with a higher scale of integration. However, optimized arithmetic blocks in course-grain reconfigurable arrays as well as field-programmable architectures still play an important role. In countless digital systems and signal processing applications, the multiplication is one of the critical challenges, where in many cases a trade-off between area usage and data throughput has to be made. But the a priori choice of word-length and number representation can also be replaced by a dynamic choice at run-time, in order to improve flexibility, area efficiency and the level of parallelism in computation. In this contribution, we look at an adaptive computing system called 3-D-SoftChip to point out what parameters are crucial to implement flexible multiplier blocks into optimized elements for accelerated processing. The 3-D-SoftChip architecture uses a novel approach to 3-dimensional integration based on flip-chip bonding with indium bumps. The modular construction, the introduction of interfaces to realize the exchange of intermediate data, and the reconfigurable sign handling approach will be explained, as well as a beneficial way to handle and distribute the numerous required control signals.

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CHO, KILSEOK, ALAN D. GEORGE, RAJ SUBRAMANIYAN, and KEONWOOK KIM. "PARALLEL ALGORITHMS FOR ADAPTIVE MATCHED-FIELD PROCESSING ON DISTRIBUTED ARRAY SYSTEMS." Journal of Computational Acoustics 12, no. 02 (June 2004): 149–74. http://dx.doi.org/10.1142/s0218396x04002274.

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Matched-field processing (MFP) localizes sources more accurately than plane-wave beamforming by employing full-wave acoustic propagation models for the cluttered ocean environment. The minimum variance distortionless response MFP (MVDR–MFP) algorithm incorporates the MVDR technique into the MFP algorithm to enhance beamforming performance. Such an adaptive MFP algorithm involves intensive computational and memory requirements due to its complex acoustic model and environmental adaptation. The real-time implementation of adaptive MFP algorithms for large surveillance areas presents a serious computational challenge where high-performance embedded computing and parallel processing may be required to meet real-time constraints. In this paper, three parallel algorithms based on domain decomposition techniques are presented for the MVDR–MFP algorithm on distributed array systems. The parallel performance factors in terms of execution times, communication times, parallel efficiencies, and memory capacities are examined on three potential distributed systems including two types of digital signal processor arrays and a cluster of personal computers. The performance results demonstrate that these parallel algorithms provide a feasible solution for real-time, scalable, and cost-effective adaptive beamforming on embedded, distributed array systems.

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Garmash, Vitaliy, Yuriy Petrov, Andrey Andreev, and Anatoly Zaitsev. "Adaptive Matching of the Radar Signal and Image Display Device Dynamic Ranges." International Journal of Mathematical, Engineering and Management Sciences 4, no. 6 (December 1, 2019): 1448–58. http://dx.doi.org/10.33889/ijmems.2019.4.6-114.

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This article presents nonlinear radar signal processing method to form an image of the Earth's surface. The method proposes to match the dynamic ranges of the received signal and of the visualization device. The essence of the method is adaptive nonlinear signal processing, which provides better local contrast of radar images and improves discrimination of individual objects. The computational complexity of the proposed algorithm is optimized and allows real-time implementation in the airborne computing systems with limited computational power. Objects with large RCS merged into large illuminated "spots"; their visibility on the surrounding background has been reduced, unwanted effects are due to the fact that the above algorithms have a single point effect. To overcome the problems, the «Retinex» algorithm is usually used. They do not take into account the local neighborhood of pixels; therefore, in cases where the image contains both highly dark and strongly light local areas, these algorithms cannot provide high-quality matching of dynamic ranges.

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Yu, Zhenhao, Fang Liu, Yinquan Yuan, Sihan Li, and Zhengying Li. "Signal Processing for Time Domain Wavelengths of Ultra-Weak FBGs Array in Perimeter Security Monitoring Based on Spark Streaming." Sensors 18, no. 9 (September 4, 2018): 2937. http://dx.doi.org/10.3390/s18092937.

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To detect perimeter intrusion accurately and quickly, a stream computing technology was used to improve real-time data processing in perimeter intrusion detection systems. Based on the traditional density-based spatial clustering of applications with noise (T-DBSCAN) algorithm, which depends on manual adjustments of neighborhood parameters, an adaptive parameters DBSCAN (AP-DBSCAN) method that can achieve unsupervised calculations was proposed. The proposed AP-DBSCAN method was implemented on a Spark Streaming platform to deal with the problems of data stream collection and real-time analysis, as well as judging and identifying the different types of intrusion. A number of sensing and processing experiments were finished and the experimental data indicated that the proposed AP-DBSCAN method on the Spark Streaming platform exhibited a fine calibration capacity for the adaptive parameters and the same accuracy as the T-DBSCAN method without the artificial setting of neighborhood parameters, in addition to achieving good performances in the perimeter intrusion detection systems.

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Chen, Kuan-Ting, Wei-Hsuan Ma, Yin-Tsung Hwang, and Kuan-Ying Chang. "A Low Complexity, High Throughput DoA Estimation Chip Design for Adaptive Beamforming." Electronics 9, no. 4 (April 13, 2020): 641. http://dx.doi.org/10.3390/electronics9040641.

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Direction of Arrival (DoA) estimation is essential to adaptive beamforming widely used in many radar and wireless communication systems. Although many estimation algorithms have been investigated, most of them focus on the performance enhancement aspect but overlook the computing complexity or the hardware implementation issues. In this paper, a low-complexity yet effective DoA estimation algorithm and the corresponding hardware accelerator chip design are presented. The proposed algorithm features a combination of signal sub-space projection and parallel matching pursuit techniques, i.e., applying signal projection first before performing matching pursuit from a codebook. This measure helps minimize the interference from noise sub-space and makes the matching process free of extra orthogonalization computations. The computing complexity can thus be reduced significantly. In addition, estimations of all signal sources can be performed in parallel without going through a successive update process. To facilitate an efficient hardware implementation, the computing scheme of the estimation algorithm is also optimized. The most critical part of the algorithm, i.e., calculating the projection matrix, is largely simplified and neatly accomplished by using QR decomposition. In addition, the proposed scheme supports parallel matches of all signal sources from a beamforming codebook to improve the processing throughput. The algorithm complexity analysis shows that the proposed scheme outperforms other well-known estimation algorithms significantly under various system configurations. The performance simulation results further reveal that, subject to a beamforming codebook with a 5° angular resolution, the Root Mean Square (RMS) error of angle estimations is only 0.76° when Signal to Noise Ratio (SNR) = 20 dB. The estimation accuracy outpaces other matching pursuit based approaches and is close to that of the classic Estimation of Signal Parameters Via Rotational Invariance Techniques (ESPRIT) scheme but requires only one fifth of its computing complexity. In developing the hardware accelerator design, pipelined Coordinate Rotation Digital Computer (CORDIC) processors consisting of simple adders and shifters are employed to implement the basic trigonometric operations needed in QR decomposition. A systolic array architecture is developed as the computing kernel for QR decomposition. Other computing modules are also realized using various linear systolic arrays and chained together seamlessly to maximize the computing throughput. A Taiwan Semiconductor Manufacturing Company (TSMC) 40 nm CMOS process was chosen as the implementation technology. The gate count of the chip design is 454.4k, featuring a core size of 0.76 mm 2 , and can operate up to 333 MHz. This suggests that one DoA estimation, with up to three signal sources, can be performed every 2.38 μs.

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Herment, A., and J. F. Giovannelli. "An Adaptive Approach to Computing the Spectrum and Mean Frequency of Doppler Signals." Ultrasonic Imaging 17, no. 1 (January 1995): 1–26. http://dx.doi.org/10.1177/016173469501700101.

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Modern ultrasound Doppler systems are facing the problem of processing increasingly shorter data sets. Spectral analysis of the strongly nonstationary Doppler signal needs to shorten the analysis window while maintaining a low variance and high resolution spectrum. Color flow imaging requires estimation of the Doppler mean frequency from even shorter Doppler data sets to obtain both a high frame rate and high spatial resolution. We reconsider these two estimation problems in light of adaptive methods. A regularized parametric method for spectral analysis as well as an adapted mean frequency estimator are developed. The choice of the adaptive criterion is then addressed and adaptive spectral and mean frequency estimators are developed to minimize the mean square error on estimation in the presence of noise. Two suboptimal spectral and mean-frequency estimators are then derived for real-time applications. Finally, their performance is compared to that of both the FFT based periodogram and the AR parametric spectral analysis for the spectral estimator, and, to both the correlation angle and the Kristoffersen's [8] estimators for the mean frequency estimator using Doppler data recorded in vitro.

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FATEMIZADEH, EMAD, and PARISA SHOOSHTARI. "ROI-BASED 3D HUMAN BRAIN MAGNETIC RESONANCE IMAGES COMPRESSION USING ADAPTIVE MESH DESIGN AND REGION-BASED DISCRETE WAVELET TRANSFORM." International Journal of Wavelets, Multiresolution and Information Processing 08, no. 03 (May 2010): 407–30. http://dx.doi.org/10.1142/s0219691310003559.

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Due to the large volume required for medical images for transmission and archiving purposes, the compression of medical images is known as one of the main concepts of medical image processing. Lossless compression methods have the drawback of a low compression ratio. In contrast, lossy methods have a higher compression ratio and suffer from lower quality of the reconstructed images in the receiver. Recently, some selective compression methods have been proposed in which the main image is divided into two separate regions: Region of Interest (ROI), which should be compressed in a lossless manner, and Region of Background (ROB), which is compressed in a lossy manner with a lower quality. In this research, we introduce a new selective compression method to compress 3D brain MR images. To this aim, we design an adaptive mesh on the first slice and estimate the gray levels of the next slices by computing the mesh element's deformations. After computing the residual image, which is the difference between the main image and the estimated one, we transform it to the wavelet domain using a region-based discrete wavelet transform (RBDWT). Finally, the wavelet coefficients are coded by an object-based SPIHT coder.

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Zhang, Ying, Yubin Zhu, Kaining Han, Junchao Wang, and Jianhao Hu. "A High-Accuracy Stochastic FIR Filter with Adaptive Scaling Algorithm and Antithetic Variables Method." Electronics 10, no. 16 (August 11, 2021): 1937. http://dx.doi.org/10.3390/electronics10161937.

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Digital filter is an important fundamental component in digital signal processing (DSP) systems. Among the digital filters, the finite impulse response (FIR) filter is one of the most commonly used schemes. As a low-complexity hardware implementation technique, stochastic computing has been applied to overcome the huge hardware cost problem of high-order FIR filters. However, the stochastic FIR filter (SFIR) scheme suffers from long processing latency and accuracy degradation. In this paper, the bit stream representation noise is theoretically analyzed, and an adaptive scaling algorithm (ASA) is proposed to improve the accuracy of SFIR with the same bit stream length. Furthermore, a novel antithetic variables method is proposed to further improve the accuracy. According to the simulation results on a 64-tap FIR filter, the ASA and AV methods gain 17 dB and 6 dB on the signal-to-noise ratio (SNR), respectively. The hardware implementation results are also presented in this paper, which illustrates that the proposed ASA-AV-SFIR filter increases 4.6 times hardware efficiency with respect to the existing SFIR schemes.

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HAYASHI, Naoki, Toshimitsu USHIO, and Takafumi KANAZAWA. "Adaptive Arbitration of Fair QoS Based Resource Allocation in Multi-Tier Computing Systems." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E93-A, no. 9 (2010): 1678–83. http://dx.doi.org/10.1587/transfun.e93.a.1678.

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Liu, Li, Tao Yao, Xin Hu, Chunjie Zhou, Dianli Hou, Shulin Feng, and Hongyong Yang. "Distributed State Estimation for Dynamic Positioning Systems with Uncertain Disturbances and Transmission Time Delays." Complexity 2020 (July 20, 2020): 1–15. http://dx.doi.org/10.1155/2020/7698504.

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The dynamic positioning system of unmanned underwater vehicles (UUVs) is a complex and large-scale system mainly due to the nonlinear dynamics, uncertainty in model parameters, and external disturbances. With the aid of the bio-inspired computing (BIC) method, the designed three-dimensional (3D) spatial positioning system is used for enlarging communication constraints and increasing signal coordination processing. With the growing of measurement scales, the issue of the networked high-precision positioning has been developed rapidly. Then, an information fusion estimation approach is presented for the distributed networked systems with data random transmission time delays and lost and disordered packets. To reduce the communication burden, an adaptive signal selection scheme is employed to reorganize the measurement sequence, and the parameter uncertainties as well as cross-correlated noise are used to describe the uncertain disturbances. Moreover, a reoptimal weighted fusion state estimation is designed to alleviate the information redundancy and maintain higher measurement accuracy. An illustrative example obtained from the 3D spatial positioning system is given to validate the effectiveness of the proposed method.

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Dissertations / Theses on the topic "Adaptive computing systems Signal processing"

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Myjak, Mitchell John. "A medium-grain reconfigurable architecture for digital signal processing." Online access for everyone, 2006. http://www.dissertations.wsu.edu/Dissertations/Spring2006/m%5Fmyjak%5F042706.pdf.

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Skarpas, Daniel. "CAD tool emulation for a two-level reconfigurable DSP architecture." Online access for everyone, 2007. http://www.dissertations.wsu.edu/Thesis/Spring2007/D_Skarpas_050407.pdf.

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Larson, Jonathan Karl. "CAD tool emulation for a two-level reconfigurable cell array for digital signal processing." Online access for everyone, 2005. http://www.dissertations.wsu.edu/Thesis/Fall2005/j%5Flarson%5F120805.pdf.

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King, Timothy L. "Hardware interface to connect an AN/SPS-65 radar to an SRC-6E reconfigurable computer." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Mar%5FKing.pdf.

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Yoo, Heejong. "Low-Power Audio Input Enhancement for Portable Devices." Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/6821.

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With the development of VLSI and wireless communication technology, portable devices such as personal digital assistants (PDAs), pocket PCs, and mobile phones have gained a lot of popularity. Many such devices incorporate a speech recognition engine, enabling users to interact with the devices using voice-driven commands and text-to-speech synthesis. The power consumption of DSP microprocessors has been consistently decreasing by half about every 18 months, following Gene's law. The capacity of signal processing, however, is still significantly constrained by the limited power budget of these portable devices. In addition, analog-to-digital (A/D) converters can also limit the signal processing of portable devices. Many systems require very high-resolution and high-performance A/D converters, which often consume a large fraction of the limited power budget of portable devices. The proposed research develops a low-power audio signal enhancement system that combines programmable analog signal processing and traditional digital signal processing. By utilizing analog signal processing based on floating-gate transistor technology, the power consumption of the overall system as well as the complexity of the A/D converters can be reduced significantly. The system can be used as a front end of portable devices in which enhancement of audio signal quality plays a critical role in automatic speech recognition systems on portable devices. The proposed system performs background audio noise suppression in a continuous-time domain using analog computing elements and acoustic echo cancellation in a discrete-time domain using an FPGA.

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King, Graham A. "High performance computing systems for signal processing." Thesis, Southampton Solent University, 1996. http://ssudl.solent.ac.uk/2424/.

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The submission begins by demonstrating that the conditions required for consideration under the University's research degrees regulations have been met in full. There then follows a commentary which starts by explaining the origin of the research theme concerned and which continues by discussing the nature and significance of the work. This has been an extensive programme to devise new methods of improving the computational speed and efficiency required for effective implementation of FIR and IIR digital filters and transforms. The problems are analysed and initial experimental work is described which sought to quantify the performance to be derived from peripheral vector processors. For some classes of computation, especially in real time, it was necessary to tum to pure systolic array hardware engines and a large number of innovations are suggested, both in array architecture and in the creation of a new hybrid opto-electronic adder capable of improving the performance ofprocessing elements for the array. This significant and original research is extended further by including a class of computation involving a bit sliced co-processor. A means of measuring the performance of this system is developed and discussed. The contribution of the work has been evident in: software innovation for horizontal architecture microprocessors; improved multi-dimensional systolic array designs; the development of completely new implementations of processing elements in such arrays; and in the details of co-processing architectures for bit sliced microprocessors. The use of Read Only Memory in creating n-dimensional FIR or IIR filters, and in executing the discrete cosine transform is a further innovative contribution that has enabled researchers to re-examine the case for pre-calculated systems previously using stored squares. The Read Only Memory work has suggested that Read Only Memory chips may be combined in a way architecturally similar to systolic array processing elements. This led to original concepts of pipelining for memory devices. The work is entirely coherent in that it covers the application of these contributions to a set of common processes, producing a set of performance graded and scaleable solutions. In order that effective solutions are proposed it was necessary to demonstrate a solid underlying appreciation of the computational mechanics involved. Whilst the published papers within this submission assume such an understanding , two appendices are provided to demonstrate the essential groundwork necessary to underpin the work resulting in these publications. The improved results obtained from the programme were threefold: execution time; theoretical clocking speeds and circuit areas; and speed up ratios. In the case of the investigations involving vector signal processors the issue was one of quantifying the performance bounds of the architecture in performing specific combinations of signal processing functions. An important aspect of this work was the optimisation achieved in the programming of the device. The use of innovative techniques reduced the execution time for the complex combinational algorithms involved to sub 10 milliseconds. Given the real time constraints for typical applications and the aims for this research the work evolved toward dedicated hardware solutions. Systolic arrays were thus a significant area of investigation. In such systems meritorious criteria are concerned with achieving: a higher regularity in architectural structure; data exchanges only with nearest neighbour processing elements; minimised global distribution functions such as power supplies and clock lines; minimised latency; minimisation in the use of latches; the elimination of output adders; and the design of higher speed processing elements. The programme has made original and significant contributions to the art of effective array design culminating in systems calculated to clock at 100MHz when using 1 micron CMOS technology, whilst creating reductions in transistor count when compared with contemporary implementations. The improvements vary by specific design but are ofthe order of30-l00% speed advantage and 20-30% less real estate usage. The third type of result was obtained when considering operations best executed by dedicated microcode running on bit sliced engines. The main issues for this part of the work were the development of effective interactions between host processors and the bit sliced processors used for computationally intensive and repetitive functions together with the evaluation of the relative performance of new bit sliced microcode solutions. The speed up obtained relative to a range of state of the art microprocessors (68040, 80386, 32032) ranged from 2: 1 to 8: 1. The programme of research is represented by sixteen papers divided into three groups corresponding to the following stages in the work: problem definition and initial responses involving vector processors; the synthesis of higher performance solutions using dedicated hardware; and bit sliced solutions

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Hong, John Hyunchul Psaltis Demetri. "Optical computing for adaptive signal processing and associative memories /." Diss., Pasadena, Calif. : California Institute of Technology, 1987. http://resolver.caltech.edu/CaltechETD:etd-06142006-094757.

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Lorente, Giner Jorge. "Adaptive signal processing for multichannel sound using high performance computing." Doctoral thesis, Universitat Politècnica de València, 2015. http://hdl.handle.net/10251/58427.

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[EN] The field of audio signal processing has undergone a major development in recent years. Both the consumer and professional marketplaces continue to show growth in audio applications such as immersive audio schemes that offer optimal listening experience, intelligent noise reduction in cars or improvements in audio teleconferencing or hearing aids. The development of these applications has a common interest in increasing or improving the number of discrete audio channels, the quality of the audio or the sophistication of the algorithms. This often gives rise to problems of high computational cost, even when using common signal processing algorithms, mainly due to the application of these algorithms to multiple signals with real-time requirements. The field of High Performance Computing (HPC) based on low cost hardware elements is the bridge needed between the computing problems and the real multimedia signals and systems that lead to user's applications. In this sense, the present thesis goes a step further in the development of these systems by using the computational power of General Purpose Graphics Processing Units (GPGPUs) to exploit the inherent parallelism of signal processing for multichannel audio applications. The increase of the computational capacity of the processing devices has been historically linked to the number of transistors in a chip. However, nowadays the improvements in the computational capacity are mainly given by increasing the number of processing units and using parallel processing. The Graphics Processing Units (GPUs), which have now thousands of computing cores, are a representative example. The GPUs were traditionally used to graphic or image processing, but new releases in the GPU programming environments such as CUDA have allowed the use of GPUS for general processing applications. Hence, the use of GPUs is being extended to a wide variety of intensive-computation applications among which audio processing is included. However, the data transactions between the CPU and the GPU and viceversa have questioned the viability of the use of GPUs for audio applications in which real-time interaction between microphones and loudspeakers is required. This is the case of the adaptive filtering applications, where an efficient use of parallel computation in not straightforward. For these reasons, up to the beginning of this thesis, very few publications had dealt with the GPU implementation of real-time acoustic applications based on adaptive filtering. Therefore, this thesis aims to demonstrate that GPUs are totally valid tools to carry out audio applications based on adaptive filtering that require high computational resources. To this end, different adaptive applications in the field of audio processing are studied and performed using GPUs. This manuscript also analyzes and solves possible limitations in each GPU-based implementation both from the acoustic point of view as from the computational point of view.
[ES] El campo de procesado de señales de audio ha experimentado un desarrollo importante en los últimos años. Tanto el mercado de consumo como el profesional siguen mostrando un crecimiento en aplicaciones de audio, tales como: los sistemas de audio inmersivo que ofrecen una experiencia de sonido óptima, los sistemas inteligentes de reducción de ruido en coches o las mejoras en sistemas de teleconferencia o en audífonos. El desarrollo de estas aplicaciones tiene un propósito común de aumentar o mejorar el número de canales de audio, la propia calidad del audio o la sofisticación de los algoritmos. Estas mejoras suelen dar lugar a sistemas de alto coste computacional, incluso usando algoritmos comunes de procesado de señal. Esto se debe principalmente a que los algoritmos se suelen aplicar a sistemas multicanales con requerimientos de procesamiento en tiempo real. El campo de la Computación de Alto Rendimiento basado en elementos hardware de bajo coste es el puente necesario entre los problemas de computación y los sistemas multimedia que dan lugar a aplicaciones de usuario. En este sentido, la presente tesis va un paso más allá en el desarrollo de estos sistemas mediante el uso de la potencia de cálculo de las Unidades de Procesamiento Gráfico (GPU) en aplicaciones de propósito general. Con ello, aprovechamos la inherente capacidad de paralelización que poseen las GPU para procesar señales de audio y obtener aplicaciones de audio multicanal. El aumento de la capacidad computacional de los dispositivos de procesado ha estado vinculado históricamente al número de transistores que había en un chip. Sin embargo, hoy en día, las mejoras en la capacidad computacional se dan principalmente por el aumento del número de unidades de procesado y su uso para el procesado en paralelo. Las GPUs son un ejemplo muy representativo. Hoy en día, las GPUs poseen hasta miles de núcleos de computación. Tradicionalmente, las GPUs se han utilizado para el procesado de gráficos o imágenes. Sin embargo, la aparición de entornos sencillos de programación GPU, como por ejemplo CUDA, han permitido el uso de las GPU para aplicaciones de procesado general. De ese modo, el uso de las GPU se ha extendido a una amplia variedad de aplicaciones que requieren cálculo intensivo. Entre esta gama de aplicaciones, se incluye el procesado de señales de audio. No obstante, las transferencias de datos entre la CPU y la GPU y viceversa pusieron en duda la viabilidad de las GPUs para aplicaciones de audio en las que se requiere una interacción en tiempo real entre micrófonos y altavoces. Este es el caso de las aplicaciones basadas en filtrado adaptativo, donde el uso eficiente de la computación en paralelo no es sencillo. Por estas razones, hasta el comienzo de esta tesis, había muy pocas publicaciones que utilizaran la GPU para implementaciones en tiempo real de aplicaciones acústicas basadas en filtrado adaptativo. A pesar de todo, esta tesis pretende demostrar que las GPU son herramientas totalmente válidas para llevar a cabo aplicaciones de audio basadas en filtrado adaptativo que requieran elevados recursos computacionales. Con este fin, la presente tesis ha estudiado y desarrollado varias aplicaciones adaptativas de procesado de audio utilizando una GPU como procesador. Además, también analiza y resuelve las posibles limitaciones de cada aplicación tanto desde el punto de vista acústico como desde el punto de vista computacional.
[CAT] El camp del processament de senyals d'àudio ha experimentat un desenvolupament important als últims anys. Tant el mercat de consum com el professional segueixen mostrant un creixement en aplicacions d'àudio, com ara: els sistemes d'àudio immersiu que ofereixen una experiència de so òptima, els sistemes intel·ligents de reducció de soroll en els cotxes o les millores en sistemes de teleconferència o en audiòfons. El desenvolupament d'aquestes aplicacions té un propòsit comú d'augmentar o millorar el nombre de canals d'àudio, la pròpia qualitat de l'àudio o la sofisticació dels algorismes que s'utilitzen. Això, sovint dóna lloc a sistemes d'alt cost computacional, fins i tot quan es fan servir algorismes comuns de processat de senyal. Això es deu principalment al fet que els algorismes se solen aplicar a sistemes multicanals amb requeriments de processat en temps real. El camp de la Computació d'Alt Rendiment basat en elements hardware de baix cost és el pont necessari entre els problemes de computació i els sistemes multimèdia que donen lloc a aplicacions d'usuari. En aquest sentit, aquesta tesi va un pas més enllà en el desenvolupament d'aquests sistemes mitjançant l'ús de la potència de càlcul de les Unitats de Processament Gràfic (GPU) en aplicacions de propòsit general. Amb això, s'aprofita la inherent capacitat de paral·lelització que posseeixen les GPUs per processar senyals d'àudio i obtenir aplicacions d'àudio multicanal. L'augment de la capacitat computacional dels dispositius de processat ha estat històricament vinculada al nombre de transistors que hi havia en un xip. No obstant, avui en dia, les millores en la capacitat computacional es donen principalment per l'augment del nombre d'unitats de processat i el seu ús per al processament en paral·lel. Un exemple molt representatiu són les GPU, que avui en dia posseeixen milers de nuclis de computació. Tradicionalment, les GPUs s'han utilitzat per al processat de gràfics o imatges. No obstant, l'aparició d'entorns senzills de programació de la GPU com és CUDA, han permès l'ús de les GPUs per a aplicacions de processat general. D'aquesta manera, l'ús de les GPUs s'ha estès a una àmplia varietat d'aplicacions que requereixen càlcul intensiu. Entre aquesta gamma d'aplicacions, s'inclou el processat de senyals d'àudio. No obstant, les transferències de dades entre la CPU i la GPU i viceversa van posar en dubte la viabilitat de les GPUs per a aplicacions d'àudio en què es requereix la interacció en temps real de micròfons i altaveus. Aquest és el cas de les aplicacions basades en filtrat adaptatiu, on l'ús eficient de la computació en paral·lel no és senzilla. Per aquestes raons, fins al començament d'aquesta tesi, hi havia molt poques publicacions que utilitzessin la GPU per implementar en temps real aplicacions acústiques basades en filtrat adaptatiu. Malgrat tot, aquesta tesi pretén demostrar que les GPU són eines totalment vàlides per dur a terme aplicacions d'àudio basades en filtrat adaptatiu que requereixen alts recursos computacionals. Amb aquesta finalitat, en la present tesi s'han estudiat i desenvolupat diverses aplicacions adaptatives de processament d'àudio utilitzant una GPU com a processador. A més, aquest manuscrit també analitza i resol les possibles limitacions de cada aplicació, tant des del punt de vista acústic, com des del punt de vista computacional.
Lorente Giner, J. (2015). Adaptive signal processing for multichannel sound using high performance computing [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/58427
TESIS

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Chan, M. K. "Adaptive signal processing algorithms for non-Gaussian signals." Thesis, Queen's University Belfast, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.269023.

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Gerbracht, Sabrina, Eduard A. Jorswieck, Gan Zheng, and Björn Ottersten. "Non-regenerative Two-Hop Wiretap Channels using Interference Neutralization." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-113245.

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Abstract:

In this paper, we analyze the achievable secrecy rates in the two-hop wiretap channel with four nodes, where the transmitter and the receiver have multiple antennas while the relay and the eavesdropper have only a single antenna each. The relay is operating in amplify-and-forward mode and all the channels between the nodes are known perfectly by the transmitter. We discuss different transmission and protection schemes like artificial noise (AN). Furthermore, we introduce interference neutralization (IN) as a new protection scheme. We compare the different schemes regarding the high-SNR slope and the high-SNR power offset and illustrate the performance by simulation results. It is shown analytically as well as by numerical simulations that the high SNR performance of the proposed IN scheme is better than the one of AN.

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Books on the topic "Adaptive computing systems Signal processing"

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Nitzberg, Ramon. Radar signal processing and adaptive systems. Boston: Artech House, 1999.

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Adaptive Array Systems. New York: John Wiley & Sons, Ltd., 2006.

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Beckerman, Martin. Adaptive cooperative systems. New York: Wiley, 1997.

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1931-, Haykin Simon S., and Kosko Bart, eds. Intelligent signal processing. New York: IEEE Press, 2001.

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Widrow, Bernard. Adaptive inverse control: A signal processing approach. Piscataway, NJ: IEEE Press, 2008.

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B, Zarrop Martin, ed. Self-tuning systems: Control and signal processing. Chichester: Wiley, 1991.

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Signal processing for intelligent sensor systems. New York: Marcel Dekker, 2000.

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Change detection and input design in dynamical systems. Taunton, Somerset, England: Research Studies Press, 1993.

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M, Ghavami, ed. Adaptive array systems: Fundamentals and applications. Chichester, West Sussex, England: John Wiley & Sons, 2005.

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Farrell, Jay. Adaptive Approximation Based Control. New York: John Wiley & Sons, Ltd., 2006.

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Book chapters on the topic "Adaptive computing systems Signal processing"

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Meyer-Baese, Uwe. "Adaptive Systems." In Digital Signal Processing with Field Programmable Gate Arrays, 533–630. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-45309-0_8.

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ÅStröM, Karl J. "Oscillations in Systems with Relay Feedback." In Adaptive Control, Filtering, and Signal Processing, 1–25. New York, NY: Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4419-8568-2_1.

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Budko, Pavel A., Alexey M. Vinogradenko, Alexey V. Mezhenov, and Nina G. Zhuravlyova. "Method for Adaptive Control of Technical States of Radio-Electronic Systems." In Advances in Signal Processing, 137–50. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40312-6_11.

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Kokotović, Petar, and Miroslav Krstić. "A New Class of Adaptive Nonlinear Systems." In Communications, Computation, Control, and Signal Processing, 441–52. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6281-8_27.

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Kanellakopoulos, Ioannis. "Adaptive Control of Nonlinear Systems: A Tutorial." In Adaptive Control, Filtering, and Signal Processing, 89–133. New York, NY: Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4419-8568-2_5.

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Rohani, Bijan, and Kah-Seng Chung. "Adaptive Signal Equalisation for Frequency Discriminator Output Signal in a Mobile Channel." In Digital Signal Processing for Communication Systems, 187–94. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6119-4_21.

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Priya, L., A. Kandaswamy, R. P. Ajeesh, and V. Vignesh. "Adaptive Equalization Algorithm for Electrocardiogram Signal Transmission." In Advances in Intelligent Systems and Computing, 217–26. Singapore: Springer Singapore, 2015. http://dx.doi.org/10.1007/978-981-10-0251-9_22.

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Sun, Jing. "A Multilinear Parametrization Approach for Identification of Partially Known Systems." In Adaptive Control, Filtering, and Signal Processing, 359–73. New York, NY: Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4419-8568-2_17.

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Govil, Rekha. "Neural Networks in Signal Processing." In Fuzzy Systems and Soft Computing in Nuclear Engineering, 235–57. Heidelberg: Physica-Verlag HD, 2000. http://dx.doi.org/10.1007/978-3-7908-1866-6_11.

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Kelly, Joy H., and B. Erik Ydstie. "Design Guidelines for Adaptive Control with Application to Systems with Structural Flexibility." In Adaptive Control, Filtering, and Signal Processing, 135–63. New York, NY: Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4419-8568-2_6.

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Conference papers on the topic "Adaptive computing systems Signal processing"

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Schott, Brian, Peter Bellows, Matthew French, and Robert Parker. "Applications of adaptive computing systems for signal processing challenges." In the 2003 conference. New York, New York, USA: ACM Press, 2003. http://dx.doi.org/10.1145/1119772.1119868.

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Qureshi, Rizwan, Muhammad Uzair, and Khurram Khurshid. "Multistage Adaptive filter for ECG signal processing." In 2017 International Conference on Communication, Computing and Digital Systems (C-CODE). IEEE, 2017. http://dx.doi.org/10.1109/c-code.2017.7918958.

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"Adaptive Computing for Flexible, Resilient and Robust Embedded Systems." In 2019 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA). IEEE, 2019. http://dx.doi.org/10.23919/spa.2019.8936796.

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Boutellier, Jani, and Shuvra S. Bhattacharyya. "Low-power heterogeneous computing via adaptive execution of dataflow actors." In 2017 IEEE International Workshop on Signal Processing Systems (SiPS). IEEE, 2017. http://dx.doi.org/10.1109/sips.2017.8110002.

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Moorman, A. C., and D. M. Cates. "A complete development environment for image processing applications on adaptive computing systems." In 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258). IEEE, 1999. http://dx.doi.org/10.1109/icassp.1999.758362.

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Zhao, Hua-An, and Yihenew Wondie Marye. "Adaptive modulation for cooperative wireless communication systems." In 2014 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC). IEEE, 2014. http://dx.doi.org/10.1109/icspcc.2014.6986161.

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Aliobory, Kahlan, and Mehmet Akif Yazici. "An Adaptive Offloading Decision Scheme in Two-Class Mobile Edge Computing Systems." In 2018 41st International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2018. http://dx.doi.org/10.1109/tsp.2018.8441475.

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Prasad, D. K. "Adaptive traffic signal control system with cloud computing based online learning." In 2011 8th International Conference on Information, Communications & Signal Processing (ICICS 2011). IEEE, 2011. http://dx.doi.org/10.1109/icics.2011.6173581.

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Das, Madhulika, and Chitralekha Mahanta. "Optimal adaptive sliding mode controller for linear uncertain systems." In 2013 IEEE International Conference on Signal Processing, Computing and Control (ISPCC). IEEE, 2013. http://dx.doi.org/10.1109/ispcc.2013.6663457.

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Sun, Guofa, and Lifan Heng. "Command-Filtered Adaptive Recursive Sliding Control for Switched Nonlinear Systems." In 2018 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC). IEEE, 2018. http://dx.doi.org/10.1109/icspcc.2018.8567835.

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Reports on the topic "Adaptive computing systems Signal processing"

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Boehm, Wim, Bruce Draper, and Ross Beveridge. Cameron - Optimized Compilation of Visual Programs for Image Processing on Adaptive Computing Systems (ACS). Fort Belvoir, VA: Defense Technical Information Center, January 2002. http://dx.doi.org/10.21236/ada407678.

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Smith, Bradley W. Distributed Computing for Signal Processing: Modeling of Asynchronous Parallel Computation. Appendix G. On the Design and Modeling of Special Purpose Parallel Processing Systems. Fort Belvoir, VA: Defense Technical Information Center, May 1985. http://dx.doi.org/10.21236/ada167622.

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